Files
momentry_core/scripts/push_existing_embeddings.py
Accusys fd2edd5736 fix: TKG rebuild type mismatch and face_track nodes
- Fix trace_id type mismatch (INT4 vs i64) with explicit ::bigint cast
- Change build_face_track_nodes to use from_pg version
- Add skin_tone_trace_nodes to API response
- Add #[derive(Serialize)] to TkgResult
- Fix Unicode panic in text label truncation
- Add push_existing_embeddings.py script
2026-06-25 11:23:53 +08:00

88 lines
2.7 KiB
Python
Executable File

#!/opt/homebrew/bin/python3.11
"""
Push existing embeddings from face.json to Qdrant _faces collection.
This is faster than recomputing embeddings with face_processor.py.
Usage:
python scripts/push_existing_embeddings.py --file-uuid <uuid>
python scripts/push_existing_embeddings.py --all
"""
import os
import sys
import json
import argparse
from pathlib import Path
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
from utils.qdrant_faces import (
ensure_faces_collection,
push_face_embeddings_batch,
)
OUTPUT_DIR = os.environ.get("MOMENTRY_OUTPUT_DIR", "/Users/accusys/momentry/output")
def push_embeddings_for_file(file_uuid: str) -> int:
"""Push embeddings from face.json to Qdrant"""
face_json_path = Path(OUTPUT_DIR) / f"{file_uuid}.face.json"
if not face_json_path.exists():
print(f"ERROR: {face_json_path} not found")
return 0
with open(face_json_path) as f:
data = json.load(f)
faces = []
for frame_data in data.get("frames", []):
frame = frame_data.get("frame", 0)
for face in frame_data.get("faces", []):
embedding = face.get("embedding")
if not embedding:
continue
faces.append({
"frame": frame,
"trace_id": face.get("trace_id"),
"bbox": {
"x": face.get("x", 0),
"y": face.get("y", 0),
"width": face.get("width", 0),
"height": face.get("height", 0),
},
"confidence": face.get("confidence", 0),
"embedding": embedding,
})
if faces:
count = push_face_embeddings_batch(file_uuid, faces)
print(f"Pushed {count} embeddings for {file_uuid}")
return count
return 0
def main():
parser = argparse.ArgumentParser(description="Push existing embeddings to Qdrant")
parser.add_argument("--file-uuid", help="File UUID to process")
parser.add_argument("--all", action="store_true", help="Process all files in output dir")
args = parser.parse_args()
if args.all:
total = 0
for face_json in Path(OUTPUT_DIR).glob("*.face.json"):
# Extract UUID from filename like "uuid.face.json"
filename = face_json.name
file_uuid = filename.replace(".face.json", "")
count = push_embeddings_for_file(file_uuid)
total += count
print(f"\nTotal: {total} embeddings pushed")
elif args.file_uuid:
push_embeddings_for_file(args.file_uuid)
else:
parser.print_help()
if __name__ == "__main__":
main()